Optimized Sensor Placement of Water Supply Network Based on Multi-Objective White Whale Optimization Algorithm

The optimization of sensor locations in water distribution networks has been extensively studied. Previous studies of highly sensitive nodes are usually distributed in a certain area, which leads to redundant information in the sensor network. This is because these studies do not consider that the i...

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Published in:Water
Main Authors: Yihong Guan, Mou Lv, Shuyan Li, Yanbo Su, Shen Dong
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2023
Subjects:
Online Access:https://doi.org/10.3390/w15152677
https://doaj.org/article/ebab1399f74c4307bc4832352e7f8bc6
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spelling ftdoajarticles:oai:doaj.org/article:ebab1399f74c4307bc4832352e7f8bc6 2023-09-05T13:23:57+02:00 Optimized Sensor Placement of Water Supply Network Based on Multi-Objective White Whale Optimization Algorithm Yihong Guan Mou Lv Shuyan Li Yanbo Su Shen Dong 2023-07-01T00:00:00Z https://doi.org/10.3390/w15152677 https://doaj.org/article/ebab1399f74c4307bc4832352e7f8bc6 EN eng MDPI AG https://www.mdpi.com/2073-4441/15/15/2677 https://doaj.org/toc/2073-4441 doi:10.3390/w15152677 2073-4441 https://doaj.org/article/ebab1399f74c4307bc4832352e7f8bc6 Water, Vol 15, Iss 2677, p 2677 (2023) sensitivity function water supply network optimal sensor placement multi-objective White Whale Optimization multi-objective optimization Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500 article 2023 ftdoajarticles https://doi.org/10.3390/w15152677 2023-08-13T00:34:21Z The optimization of sensor locations in water distribution networks has been extensively studied. Previous studies of highly sensitive nodes are usually distributed in a certain area, which leads to redundant information in the sensor network. This is because these studies do not consider that the impact is different when a leak occurs in different nodes. In this study, sensitivity functions of different nodes were obtained according to the influence of the leakage of each node on the water distribution network. Combined with the water pressure correlation and water pressure sensitivity between nodes, the monitoring range of monitoring points and the water demand of covering nodes of monitoring points were taken as objective functions to build an optimal layout model. Taking a pipeline network in Qingdao as an example, the model was solved by using multi-objective White Whale Optimization and NSGA-II. By comparing the operation results of the four cases, it was found that the monitoring points found using multi-objective White Whale Optimization show better searching ability in terms of the sensitivity functions of different nodes. Article in Journal/Newspaper White whale Directory of Open Access Journals: DOAJ Articles Water 15 15 2677
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic sensitivity function
water supply network
optimal sensor placement
multi-objective White Whale Optimization
multi-objective optimization
Hydraulic engineering
TC1-978
Water supply for domestic and industrial purposes
TD201-500
spellingShingle sensitivity function
water supply network
optimal sensor placement
multi-objective White Whale Optimization
multi-objective optimization
Hydraulic engineering
TC1-978
Water supply for domestic and industrial purposes
TD201-500
Yihong Guan
Mou Lv
Shuyan Li
Yanbo Su
Shen Dong
Optimized Sensor Placement of Water Supply Network Based on Multi-Objective White Whale Optimization Algorithm
topic_facet sensitivity function
water supply network
optimal sensor placement
multi-objective White Whale Optimization
multi-objective optimization
Hydraulic engineering
TC1-978
Water supply for domestic and industrial purposes
TD201-500
description The optimization of sensor locations in water distribution networks has been extensively studied. Previous studies of highly sensitive nodes are usually distributed in a certain area, which leads to redundant information in the sensor network. This is because these studies do not consider that the impact is different when a leak occurs in different nodes. In this study, sensitivity functions of different nodes were obtained according to the influence of the leakage of each node on the water distribution network. Combined with the water pressure correlation and water pressure sensitivity between nodes, the monitoring range of monitoring points and the water demand of covering nodes of monitoring points were taken as objective functions to build an optimal layout model. Taking a pipeline network in Qingdao as an example, the model was solved by using multi-objective White Whale Optimization and NSGA-II. By comparing the operation results of the four cases, it was found that the monitoring points found using multi-objective White Whale Optimization show better searching ability in terms of the sensitivity functions of different nodes.
format Article in Journal/Newspaper
author Yihong Guan
Mou Lv
Shuyan Li
Yanbo Su
Shen Dong
author_facet Yihong Guan
Mou Lv
Shuyan Li
Yanbo Su
Shen Dong
author_sort Yihong Guan
title Optimized Sensor Placement of Water Supply Network Based on Multi-Objective White Whale Optimization Algorithm
title_short Optimized Sensor Placement of Water Supply Network Based on Multi-Objective White Whale Optimization Algorithm
title_full Optimized Sensor Placement of Water Supply Network Based on Multi-Objective White Whale Optimization Algorithm
title_fullStr Optimized Sensor Placement of Water Supply Network Based on Multi-Objective White Whale Optimization Algorithm
title_full_unstemmed Optimized Sensor Placement of Water Supply Network Based on Multi-Objective White Whale Optimization Algorithm
title_sort optimized sensor placement of water supply network based on multi-objective white whale optimization algorithm
publisher MDPI AG
publishDate 2023
url https://doi.org/10.3390/w15152677
https://doaj.org/article/ebab1399f74c4307bc4832352e7f8bc6
genre White whale
genre_facet White whale
op_source Water, Vol 15, Iss 2677, p 2677 (2023)
op_relation https://www.mdpi.com/2073-4441/15/15/2677
https://doaj.org/toc/2073-4441
doi:10.3390/w15152677
2073-4441
https://doaj.org/article/ebab1399f74c4307bc4832352e7f8bc6
op_doi https://doi.org/10.3390/w15152677
container_title Water
container_volume 15
container_issue 15
container_start_page 2677
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